Regularized Evolution for Image Classifier Architecture Search (REA). [1]}. For both search spaces, the population size and sample size are set to 10. We set the number of cycles as 40. Hence, a total of 50 architectures would be selected. The best validation accuracy throughout the evaluation of a network would be chosen as the fitness. For the macro-level search space, the mutation operation would be randomly adding, deleting, or changing a module type.
